Advances in NLP: Exploring Transformative Techniques and Real-World Applications
Journal Title: International Journal for Modern Trends in Science and Technology - Year 2024, Vol 10, Issue 9
Abstract
Natural Language Processing (NLP) has undergone significant advancements, leading to innovative methods and applications across various domains. Cutting-edge techniques like Transformers, Generative Adversarial Networks (GANs), and Transfer Learning have revolutionized tasks such as machine translation, sentiment analysis, and text summarization. Transformers, with their self-attention mechanisms, have notably improved contextual understanding, enabling more accurate and fluent translations, as well as powerful language models like BERT and GPT. GANs have been applied in text generation and data augmentation, pushing the boundaries of creative content generation. Transfer Learning, through pre-trained models fine-tuned for specific tasks, has enhanced efficiency and performance in NLP applications, particularly when data is scarce. These methods have fueled the development of advanced applications, including sophisticated chatbots, virtual assistants, and machine translation systems, which are transforming industries from customer service to healthcare. Sentiment analysis, powered by deep learning, is providing valuable insights into public opinion and market trends, while text summarization and information extraction are making vast amounts of textual data more accessible and actionable.
Authors and Affiliations
Dr. Suneel Pappala and Dr. D. Sasi Raja Sakar
Keywords
Related Articles
- EP ID EP747896
- DOI https://doi.org/10.46501/IJMTST1009017
- Views 79
- Downloads 0
Optimal Cascaded Terminal Sliding Mode Controller for third-order DC motor model
Applying Terminal Sliding Mode Control (TSM) for a third-order system is always challenging. Most of the cases, authors use a Cascaded type of TSM (CTSM) to control those systems. But with two separate phases of sliding...
Antidiabetic Potential of Mangifera Indica: Insights from In Vitro and In Vivo Studies
Background: Diabetes mellitus is a chronic endocrine disorder characterized by elevated blood glucose levels. Owing to the adverse side effects of synthetic drugs, natural products attract research interest because of th...
Benefits and Difficulties of Student-Generative Artificial Intelligence Collaboration in Programming Learning: An Empirical Case Study
Conversational generative artificial intelligence Gen AI is sometimes viewed as a two-edged sword that could result in learning that is only superficial. We created and implemented a programming course that emphasizes st...
Optimizing Disposal Efficiency Through Sensor-Based Automatic Dumping
Now a days with the increase in the population of India one issue which comes as a repercussion is the generation of waste. The project involves building a smart bin using an Arduino Uno board as the microcontroller-base...
Prediction of Ground Water Level using Machine Learning
Groundwater is a vital natural resource for various sectors including agriculture, industry, and domestic use. Timely and accurate prediction of groundwater levels plays a crucial role in effective water resource managem...